1. Field of the Invention
The present invention relates to digital transmitters, RF power amplifiers and amplification methods. More particularly, the present invention relates to digital transmitters, amplifiers and related methods that use adaptive techniques to linearize the gain transfer characteristics or reduce distortion emissions, such as digital predistortion.
2. Description of the Prior Art and Related Background Information
Wireless transmitters employed in RF communications systems employ RF power amplifiers as a key component and these are a major source of nonlinearity in the overall system. RF power amplifiers are devices that attempt to replicate an RF signal present at an input, producing an output signal with a much higher power level. The increase in power from the input to output is referred to as the ‘gain’ of the amplifier. When the gain is constant across the dynamic range of the input signal, the amplifier is said to be ‘linear’. Amplifiers have limited capacity in terms of power delivered because of gain and phase variances, particularly saturation at high power, which makes all practical amplifiers nonlinear when the input power level varies. The ratio of the distortion power generated relative to the signal power delivered is a measure of the non-linearity of the amplifier.
In RF communication systems, the maximum allowable non-linearity of the amplifier is specified by government agencies such as the FCC or the ITU. Because amplifiers are inherently nonlinear when operating near saturation, the linearity requirements often become the limitation on rated power delivering capability. In general, when operating near saturation, the linearity of the amplifier degrades rapidly because the incremental signal power delivered by an amplifier is proportionally less than the incremental distortion power generated.
Various compensation approaches are conventionally applied to reduce the distortion at the output of the system, which in turn increases the rated power delivering capability. One approach is digital predistortion. In digital predistortion, the RF power amplifier is part of a RF transmitter where a digital input signal is converted to an analog signal (DAC), up-converted in frequency to create a RF signal, then amplified by the RF power amplifier. The predistortion is applied to the signal while it is in a digital format to compensate for nonlinearities later in the transmit path.
The most significant nonlinearity tends to be the gain of the RF power amplifier. Gain of the power amplifier relates the amplitude and phase of the RF output signal to the RF input signal. Nonlinear gain means that the amplitude and/or phase components of the gain vary as a function of the input signal amplitude. For the gain to be linear, the amplitude and phase components must be constant over the range of input signal amplitudes. Digital predistortion compensates for these gain fluctuations by predicting the RF gain fluctuation from the digital input signal and generating a digital gain that makes the overall gain of the transmitter, the series combination of the digital and RF gains, more linear than the RF gain alone. In order to accurately predict the RF gain variations from the digital input signal, a digital model of the inverse of RF gain is required. In general, the digital model—whether it is based a look-up-table, polynomial expansion, or both—has a parametric form where the inverse gain is the sum of basis waveforms derived from the input signal weighted by a vector of complex predistortion parameters. The predistortion parameters are adjusted using an adaptive controller for optimal distortion correction and gain linearization.
Most end users of power amplifiers have specifications limiting the time that the adaptive portion can take to achieve sufficient distortion correction. As a result, it is important to have good initial predistortion parameter settings when the adaptive controller begins its search for the best (or sufficient) predistortion parameters. Some such specifications have times as low as 10 seconds.
There have been numerous prior approaches to predistortion. In earlier approaches, the compensating gain was implemented using static analog circuitry, hand-tuned to be optimal for nominal operating conditions. Later digital approaches were introduced allowing greater flexibility in the inverse gain model. Look-up-tables and polynomial expansions dependent on the instantaneous input magnitude or power only were used to model memoryless distortion. As the bandwidths of the input signal increased, usually as a result of multi-carrier signal formatting, models were expanded to be functions of both the instantaneous and past input magnitudes, capturing a type of distortion referred to as “memory-based”. Amplifiers exhibiting memory-based distortion are said to have “memory effects”.
The nonlinear gain of the RF amplifier is not only a function of the instantaneous and recent past input magnitudes (referred to as the “envelope” of the input signal), it is also influenced by other input and environmental quantities such as the average input power, the number of carriers and their center frequencies within a multi-carrier format, temperature, and DC supply voltage (collectively referred to in this disclosure as “attributes”). These attributes are characterized as measurable quantities, largely independent of the power amplifier, that vary slowly or change infrequently relative to changes in the instantaneous magnitude (envelope) of the input signal. In prior art approaches, adaptive methods are applied to re-adjust the coefficients of the inverse gain model in response to changes in the RF gain due to changes in the input or environmental quantities. A means of measuring of output signal and converting it into a digital format is required. The digital input and digitized output signals are compared to estimate the residual distortion within the output signal from which the adjustments in the predistortion parameters are computed that reduce the output distortion. In such systems, the convergence time is dependent on the size and abruptness of the change in the attribute quantities and the sensitivity of the power amplifier gain to the attributes. During the transient (converging predistortion parameter) periods, the distortion at the output might exceed the spectral mask specifications, which is not desirable.
To avoid transient distortion, the prior art has relied on look-up tables (LUT's) that are indexed using one or more of the attribute quantities. For the case where the inverse gain model is represented using a polynomial expansion, the entries of the LUT are coefficients of the expansion considered optimal for the corresponding attribute (index) quantity. For the case where the inverse gain model is also represented by LUT structure indexed to the instantaneous amplitude (envelope) of the input signal, a multi-dimensional table is formed. However, in the context of this invention, the dimensions indexed by the attribute, and not those of the envelope of the input signal, are of interest.
As indicated above, look-up tables in the past have used a fixed structure. The input, such as temperature, is an index to an array. The indices are equally spaced across the range in ascending order, and the corresponding predistortion parameters are stored within the array. The array of vectors forms a two-dimensional LUT. This structure is well suited to memory chips because the index is equivalent to an address and the predistortion parameters are equivalent to the data. However, the look-up tables are usually based on experimental data (calibration) requiring significant time to fill-in the elements of the table. In addition, drift from component aging can make any look-up table obsolete, necessitating a re-calibration.
Another difficulty with look-up tables is that it can be extremely difficult to manage multi-dimensional arrays, which would be required if many operating conditions are present which affect the optimal predistortion parameters. One can imagine the number of elements present in an equally spaced four-dimensional array. For example, 10 samples per dimension produces 10000 elements.
One technique of managing multiple indexing dimensions is to assume that the effects are separable. Separable conditions would allow the use of individual arrays for each operating condition, and the composite effect would be the sum of the individual adjustments. (Not unlike a Taylor series expansion where the partial derivatives are specified). Unfortunately, this approach is valid only for small (differential) alignment adjustments because any cross-correlation between dimensions is ignored. The largest error would occur at the corners of the multi-dimensional array. For example, a troublesome corner in the temperature, DC supply index space would be high temperature and low voltage. It is these corner locations that are tested, typically, by sophisticated customers for determining if the amplifier is compliant with specifications.
A related problem with the array-based look-up table is the selection of the sampling interval (separation between adjacent indices) within the index space. In general, the sensitivities of the predistortion parameter settings vary over the index space. The sampling density must be selected based on the most sensitive region of the index space. The remaining regions will be over-sampled. This problem of over-sampling is made more significant for multi-dimensional arrays.
There have been attempts to make look-up tables self-calibrating or self-generating. However, the fixed array structure is difficult to manage. The key problem encountered is ‘update fragmentation’. Consider the previously-mentioned four-dimensional array case. When the look-up table is updated, only one element of 10000 is changed. If the source of the degradation is global (due to component drift, for example), then all 10000 elements are affected. However, the changes must propagate as each index is visited. The potential for neighboring indices to have large differences exists, simply because one of the indices is older.
Accordingly, a need presently exists for a system and method for rapid predistortion parameter control in a digital predistortion amplifier system which avoids the above noted limitations of the prior art.